Recently, researchers from DeepMind, UC Berkeley and the University of Oxford introduced a knowledge distillation strategy for injecting syntactic biases into BERT pre-training in order to benchmark natural language understanding. Bidirectional Encoder Representation from Transformers or BERT is one of the most popular neural network-based techniques for natural language processing (NLP) while pre-training.  At the…

The post How Syntactic Biases Help BERT To Achieve Better Language Understanding appeared first on Analytics India Magazine.